Generative AI Bootcamp 2025

Build Generative AI applications using LangChain, RAG. Build multi agentic AI systems using Crew AI. Master LLMs.

• Learn how to download and install Anaconda Distribution, Jupyter notebook, Visual Studio Code

• Learn how to use Jupyter notebook 'Markdown' features

• Learn how to install CUDA Toolkit, cuDNN, PyTorch and how to enable GPU

• Learn Python basics - Introduction, Package Installation, Package Import, Variables, Identifiers, Type conversion, Read input from keyboard, Control statements and Loops, Functions, string, Data Structures - list, tuple, set, dict

• Learn what is Artificial intelligence, Machine Learning, Deep Learning and Generative AI; And, the history of AI;

• Understand the attention mechanism and how transformers encode and decode data

• Understand what are the Foundation Models, history, Applications, types, examples of foundation models.

• Understand Language Model Performance; Top Open-Source LLMs; How to Select the right Foundation Model?

• Learn Responsible AI practices and the importance of addressing biases

• Learn how to build Generative AI applications Using LangChain, RAG

• Learn what is RAG(Retrieval-Augmented Generation) and deep dive on preparing input, chunking methods, embeddings, vector store, similarity search, RAG pipeline

• Understand Vector Databases for RAG Systems: Pinecone, Chroma, Weaviate, Milvus, FAISS

• Learn different Text Chunking Methods in RAG Systems and how to choosing a chunking Method

  • Character Text Splitter Chunking Method

  • Recursive Character Text Splitter Chunking Method

  • Markdown Header Text Splitter Chunking Method

  • Token Text Splitter Chunking Method

• Learn what is Prompt Engineering

• Learn how to create OpenAI account and how to generate API key

• Learn different prompt engineering techniques

  • Basic prompt

  • Role Task Context Prompt

  • Few shot Prompting

  • Chain of thought Prompting

  • Constrained Output Prompting

• Understand Document Loaders - CSVLoader, HTMLLoader, PDFLoaders

• Learn how to provide memory to Large Language Models(LLM)

• Learn different memory types - ConversationBufferMemory, Conversation Buffer Window, ConversationSummaryMemory

• Learn how to chain different LangChain components

• Learn different chains - Single Chain, Simple Sequential Chain, Sequential Chain, Math Chain, RAG Chain, Router Chain, LLM Router Chain, SQL Chain

• Learn how to build multi agentic frameworks using CrewAI and LangChain tools

• Learn what is Hugging Face and how to use the models from Hugging Face and build Generative AI applications